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This paper describes the implementation and the evaluation of 19 Chronic Inflammatory Demyelinating Polyneuropathy (CIDP) diagnostic criteria in a Hospital Information System (HIS) that contains more than 26,000 Motor Nerve Conduction Studies (MNCS), integrated with a Knowledge Based System (KBS) that contains and applies neurological knowledge, including the CIDP criteria. The comparison, conducted on 3750 manual reviewed cases, gave very different results in terms of sensibility and specificity with no one single criterion satisfying for both. Based on personal experience, variations of these CIDP criteria were tried, but the results were not improved. Then a radically different approach was developed, programming the HIS-KBS to “discover” better criteria in order of their ability to comply with the manual review of cases. The result was a strong reduction of false positives with minimal loss of sensibility. By "reverse engineering" of the computer generated criteria it was possible to obtain some new interesting neurologic suggestions such as the role of H reflex. In conclusion, four points appear of general interest: 1) a large HIS-KBS is fundamental for developing and testing diagnostic criteria and medical procedures, particularly when they are complex; 2) “Computer aided discovery” may create rules that allows the KBS to replicate the human expertise; 3) "reverse engineering" on computer generated rules may suggest new physiopathological considerations; 4) this methodology has general application to many other fields of medicine.

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A Knowledge-Based System for Evaluation of CIDP Diagnostic Criteria in a Database with 26,000 Nerve Conduction Studies: Computer-Aided Creation of Heuristic Rules and Discovery of New Diagnostic Criteria